{"list":"other","total":126,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"1502.03167","title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","created":"2015-02-11","cited_by_count":7005},{"id":"1411.4038","title":"Fully Convolutional Networks for Semantic Segmentation","created":"2014-11-14","cited_by_count":4859},{"id":"1606.00915","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","created":"2016-06-02","cited_by_count":3241},{"id":"1802.02611","title":"Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation","created":"2018-02-07","cited_by_count":3223},{"id":"1606.03498","title":"Improved Techniques for Training GANs","created":"2016-06-10","cited_by_count":2970},{"id":"1804.02767","title":"YOLOv3: An Incremental Improvement","created":"2018-04-08","cited_by_count":2659},{"id":"1612.01105","title":"Pyramid Scene Parsing Network","created":"2016-12-04","cited_by_count":2479},{"id":"1610.02357","title":"Xception: Deep Learning with Depthwise Separable Convolutions","created":"2016-10-07","cited_by_count":2332},{"id":"1706.05587","title":"Rethinking Atrous Convolution for Semantic Image Segmentation","created":"2017-06-17","cited_by_count":2161},{"id":"1511.06434","title":"Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks","created":"2015-11-19","cited_by_count":2054},{"id":"1905.02244","title":"Searching for MobileNetV3","created":"2019-05-06","cited_by_count":1994},{"id":"1603.05027","title":"Identity Mappings in Deep Residual Networks","created":"2016-03-16","cited_by_count":1965},{"id":"1602.07261","title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning","created":"2016-02-23","cited_by_count":1512},{"id":"1506.02025","title":"Spatial Transformer Networks","created":"2015-06-05","cited_by_count":1429},{"id":"1707.01083","title":"ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices","created":"2017-07-04","cited_by_count":1200},{"id":"1607.08022","title":"Instance Normalization: The Missing Ingredient for Fast Stylization","created":"2016-07-27","cited_by_count":1198},{"id":"1511.07122","title":"Multi-Scale Context Aggregation by Dilated Convolutions","created":"2015-11-23","cited_by_count":1133},{"id":"1911.09070","title":"EfficientDet: Scalable and Efficient Object Detection","created":"2019-11-20","cited_by_count":1020},{"id":"1809.02983","title":"Dual Attention Network for Scene Segmentation","created":"2018-09-09","cited_by_count":1003},{"id":"1502.00956","title":"ORB-SLAM: a Versatile and Accurate Monocular SLAM System","created":"2015-02-03","cited_by_count":988},{"id":"1609.03677","title":"Unsupervised Monocular Depth Estimation with Left-Right Consistency","created":"2016-09-13","cited_by_count":820},{"id":"1610.06475","title":"ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras","created":"2016-10-20","cited_by_count":806},{"id":"1704.07813","title":"Unsupervised Learning of Depth and Ego-Motion from Video","created":"2017-04-25","cited_by_count":782},{"id":"1703.00848","title":"Unsupervised Image-to-Image Translation Networks","created":"2017-03-02","cited_by_count":603},{"id":"1504.06375","title":"Holistically-Nested Edge Detection","created":"2015-04-24","cited_by_count":592},{"id":"1807.05511","title":"Object Detection with Deep Learning: A Review","created":"2018-07-15","cited_by_count":528},{"id":"1805.01934","title":"Learning to See in the Dark","created":"2018-05-04","cited_by_count":460},{"id":"1911.11907","title":"GhostNet: More Features from Cheap Operations","created":"2019-11-27","cited_by_count":410},{"id":"1911.11929","title":"CSPNet: A New Backbone that can Enhance Learning Capability of CNN","created":"2019-11-27","cited_by_count":381},{"id":"1811.08883","title":"Rethinking ImageNet Pre-training","created":"2018-11-21","cited_by_count":377},{"id":"1603.04992","title":"Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue","created":"2016-03-16","cited_by_count":368},{"id":"1602.03012","title":"EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos","created":"2016-02-09","cited_by_count":367},{"id":"1709.03410","title":"One-Shot Learning for Semantic Segmentation","created":"2017-09-11","cited_by_count":337},{"id":"1604.05144","title":"ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation","created":"2016-04-18","cited_by_count":331},{"id":"1506.02106","title":"What's the Point: Semantic Segmentation with Point Supervision","created":"2015-06-06","cited_by_count":298},{"id":"2005.04757","title":"A Simple Semi-Supervised Learning Framework for Object Detection","created":"2020-05-10","cited_by_count":282},{"id":"1704.08545","title":"ICNet for Real-Time Semantic Segmentation on High-Resolution Images","created":"2017-04-27","cited_by_count":261},{"id":"1904.05044","title":"Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations","created":"2019-04-10","cited_by_count":247},{"id":"1812.05038","title":"Long-Term Feature Banks for Detailed Video Understanding","created":"2018-12-12","cited_by_count":239},{"id":"1903.02740","title":"CE-Net: Context Encoder Network for 2D Medical Image Segmentation","created":"2019-03-07","cited_by_count":220},{"id":"1801.00631","title":"Deep Learning: A Critical Appraisal","created":"2018-01-02","cited_by_count":217},{"id":"1707.03718","title":"LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation","created":"2017-06-14","cited_by_count":214},{"id":"2011.02910","title":"Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers","created":"2020-11-05","cited_by_count":190},{"id":"1902.09513","title":"FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation","created":"2019-02-25","cited_by_count":178},{"id":"1702.08502","title":"Understanding Convolution for Semantic Segmentation","created":"2017-02-27","cited_by_count":168},{"id":"1805.10180","title":"Pyramid Attention Network for Semantic Segmentation","created":"2018-05-25","cited_by_count":149},{"id":"2008.01183","title":"Weakly-Supervised Semantic Segmentation via Sub-category Exploration","created":"2020-08-03","cited_by_count":145},{"id":"1711.06897","title":"Single-Shot Refinement Neural Network for Object Detection","created":"2017-11-18","cited_by_count":129},{"id":"1701.06482","title":"Surgical Data Science: Enabling Next-Generation Surgery","created":"2017-01-23","cited_by_count":126},{"id":"2011.02284","title":"Surgical Data Science -- from Concepts toward Clinical Translation","created":"2020-10-30","cited_by_count":105},{"id":"2101.01133","title":"Stereo Correspondence and Reconstruction of Endoscopic Data Challenge","created":"2021-01-04","cited_by_count":103},{"id":"1611.03199","title":"Low Data Drug Discovery with One-shot Learning","created":"2016-11-10","cited_by_count":91},{"id":"1803.01207","title":"Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning","created":"2018-03-03","cited_by_count":81},{"id":"2103.16525","title":"Endo-Depth-and-Motion: Reconstruction and Tracking in Endoscopic Videos using Depth Networks and Photometric Constraints","created":"2021-03-30","cited_by_count":81},{"id":"2007.05533","title":"ISINet: An Instance-Based Approach for Surgical Instrument Segmentation","created":"2020-07-10","cited_by_count":67},{"id":"1907.07899","title":"Incorporating Temporal Prior from Motion Flow for Instrument Segmentation in Minimally Invasive Surgery Video","created":"2019-07-18","cited_by_count":64},{"id":"1711.06606","title":"Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training","created":"2017-11-17","cited_by_count":57},{"id":"1802.08774","title":"Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks","created":"2018-02-24","cited_by_count":57},{"id":"1903.02306","title":"Video-based surgical skill assessment using 3D convolutional neural networks","created":"2019-03-06","cited_by_count":57},{"id":"1701.00794","title":"Constrained Deep Weak Supervision for Histopathology Image Segmentation","created":"2017-01-03","cited_by_count":51},{"id":"1902.07766","title":"Dense Depth Estimation in Monocular Endoscopy with Self-supervised Learning Methods","created":"2019-02-20","cited_by_count":47},{"id":"2005.03501","title":"Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room","created":"2020-05-07","cited_by_count":47},{"id":"2107.00229","title":"E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception","created":"2021-07-01","cited_by_count":46},{"id":"2004.06816","title":"Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision","created":"2020-04-14","cited_by_count":40},{"id":"1808.08834","title":"Real-Time MDNet","created":"2018-08-27","cited_by_count":39},{"id":"1907.02882","title":"Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation","created":"2019-07-05","cited_by_count":38},{"id":"1805.02475","title":"Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery","created":"2018-05-07","cited_by_count":37},{"id":"1907.11454","title":"Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video","created":"2019-07-26","cited_by_count":36},{"id":"1812.01366","title":"Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos","created":"2018-12-04","cited_by_count":35},{"id":"2007.02501","title":"Learning Motion Flows for Semi-supervised Instrument Segmentation from Robotic Surgical Video","created":"2020-07-06","cited_by_count":35},{"id":"1705.08260","title":"Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery","created":"2017-05-17","cited_by_count":34},{"id":"1711.09726","title":"Exploiting the potential of unlabeled endoscopic video data with self-supervised learning","created":"2017-11-27","cited_by_count":33},{"id":"1710.11216","title":"Deep Learning and Conditional Random Fields-based Depth Estimation and Topographical Reconstruction from Conventional Endoscopy","created":"2017-10-30","cited_by_count":31},{"id":"1706.08126","title":"ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools","created":"2017-06-25","cited_by_count":30},{"id":"1702.07772","title":"Video and Accelerometer-Based Motion Analysis for Automated Surgical Skills Assessment","created":"2017-02-24","cited_by_count":28},{"id":"2003.03472","title":"SuPer Deep: A Surgical Perception Framework for Robotic Tissue Manipulation using Deep Learning for Feature Extraction","created":"2020-03-07","cited_by_count":28},{"id":"1909.10360","title":"RAUNet: Residual Attention U-Net for Semantic Segmentation of Cataract Surgical Instruments","created":"2019-09-23","cited_by_count":27},{"id":"2203.15251","title":"Exploring Intra- and Inter-Video Relation for Surgical Semantic Scene Segmentation","created":"2022-03-29","cited_by_count":27},{"id":"1907.00283","title":"SLAM Endoscopy enhanced by adversarial depth prediction","created":"2019-06-29","cited_by_count":26},{"id":"2007.09107","title":"Synthetic and Real Inputs for Tool Segmentation in Robotic Surgery","created":"2020-07-17","cited_by_count":25},{"id":"1703.10701","title":"Concurrent Segmentation and Localization for Tracking of Surgical Instruments","created":"2017-03-30","cited_by_count":24},{"id":"1902.08994","title":"U-NetPlus: A Modified Encoder-Decoder U-Net Architecture for Semantic and Instance Segmentation of Surgical Instrument","created":"2019-02-24","cited_by_count":23},{"id":"2003.08502","title":"Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment","created":"2020-03-18","cited_by_count":23},{"id":"2007.11319","title":"Real-Time Instrument Segmentation in Robotic Surgery using Auxiliary Supervised Deep Adversarial Learning","created":"2020-07-22","cited_by_count":23},{"id":"1703.08580","title":"Deep Residual Learning for Instrument Segmentation in Robotic Surgery","created":"2017-03-24","cited_by_count":22},{"id":"2008.00936","title":"Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection","created":"2020-07-29","cited_by_count":22},{"id":"1708.02108","title":"Two-Phase Learning for Weakly Supervised Object Localization","created":"2017-08-07","cited_by_count":21},{"id":"2010.09409","title":"SD-DefSLAM: Semi-Direct Monocular SLAM for Deformable and Intracorporeal Scenes","created":"2020-10-19","cited_by_count":21},{"id":"2107.04644","title":"Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images","created":"2021-07-09","cited_by_count":21},{"id":"1806.05573","title":"Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos","created":"2018-06-14","cited_by_count":20},{"id":"2007.11514","title":"Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation","created":"2020-07-22","cited_by_count":20},{"id":"2112.08189","title":"ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic Surgery","created":"2021-12-10","cited_by_count":20},{"id":"2107.11091","title":"Class-Incremental Domain Adaptation with Smoothing and Calibration for Surgical Report Generation","created":"2021-07-23","cited_by_count":18},{"id":"1907.00214","title":"Learning Where to Look While Tracking Instruments in Robot-assisted Surgery","created":"2019-06-29","cited_by_count":17},{"id":"2111.04911","title":"Real-time Instance Segmentation of Surgical Instruments using Attention and Multi-scale Feature Fusion","created":"2021-11-09","cited_by_count":17},{"id":"2003.04772","title":"Multi-Task Recurrent Neural Network for Surgical Gesture Recognition and Progress Prediction","created":"2020-03-10","cited_by_count":16},{"id":"1910.11109","title":"Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments","created":"2019-10-24","cited_by_count":15}],"next_cursor":"100"}